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The Alara T210 Computed Radiography System is indicated for use in generating radiographic images of human anatomy. It is intended to replace radiographic filmscreen systems in all general-purpose diagnostic procedures. The T210 is not indicated for use in mammography.

The Alara T210 is a desktop Computed Radiography (CR) system designed to generate digital x-ray images by reading photostimulable phosphor imaging plates exposed using standard x-ray systems and techniques. The system consists of a CR read or iposeing plates, and cassettes. A computer workstation and OC Acquisition software, will be optionally provided by either Alara or the distribution channel.

The provided document describes the Alara T210 Computed Radiography System as a modification of a predicate device (CRystalView T-Series Computed Radiography System, K071682). The rationale for substantial equivalence is based on the new device having the same indications for use and similar technological characteristics, with the main change being image size and system form factor.

The document does not provide detailed information on specific acceptance criteria or a dedicated study with performance metrics for the Alara T210. Instead, it states that "Alara has performed laboratory studies comparing the T210's performance characteristics to those for the predicate," and concludes that "Performance testing of the Alara T210 Computed Radiography system has demonstrated that it is substantially equivalent to the predicate device."

Therefore, I cannot fill out all parts of your request as the information is not present in the provided text.

Here's a summary of what can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Not explicitly provided. The document states that the new device's performance characteristics were compared to the predicate device, but no specific performance metrics or acceptance criteria are detailed.

2. Sample size used for the test set and the data provenance

Not provided. The document mentions "laboratory studies" and "performance testing" but does not specify sample sizes or data provenance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not provided. There is no mention of expert involvement in establishing ground truth for any test set.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

Not provided.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

No. The device is a Computed Radiography System, not an AI-powered diagnostic tool. Therefore, an MRMC study comparing human readers with and without AI assistance is not applicable and was not performed.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Yes, implicitly. The "performance testing" and "laboratory studies" would have evaluated the device itself (the CR system's image generation capabilities) which is a standalone performance by definition for such a device. However, no specific metrics or study details are provided.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

Not provided. Given that the device generates radiographic images, the "ground truth" for evaluating image quality would likely involve metrics such as spatial resolution, contrast resolution, detective quantum efficiency (DQE), MTF (Modulation Transfer Function), and noise characteristics, which are objectively measurable rather than based on expert consensus for clinical findings, pathology, or outcomes for a diagnostic claim. However, the document does not specify which of these or other metrics were used.

8. The sample size for the training set

Not applicable. This device is a Computed Radiography system for image acquisition, not an AI or machine learning algorithm that requires a training set in the conventional sense.

9. How the ground truth for the training set was established

Not applicable. (See point 8)

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The CRystalView T-Series is indicated for use in generating radiographic images of human anatomy. It is intended to replace radiographic film/screen systems in general-purpose diagnostic procedures. The CRystalView T-Series is not indicated for use in mammography.

The CRystal View T-Series System is an electrostatic X-ray imaging system that employs storage phosphor plates in place of conventional X-ray film for radiographic imaging applications. The system provides image data that must then be viewed with an external computer and appropriate software. The CRystal View T-Series System is comprised of the following functional components: Reusable storage phosphor plates, multiple sizes; Plate carousels, corresponding to reusable storage phosphor plate size; The CRystal View T-Series Scanner, an image reader /digitizer. The CRystal View T-Series Scanner / Communications Interface, USB 2.0; Optional Integrated phosphor plate eraser; CRystal View T-Series control software and a user or distribution channel-supplied computer system. Image data is sent via a dedicated connection from the CRystalView T-Series Scanner to the computer system, where it is processed and displayed for review.

The provided text is a 510(k) summary for the Alara CRystalView® T-Series Computed Radiography System. It describes the device, its intended use, and its substantial equivalence to predicate devices. However, it does not contain a detailed study proving the device meets specific acceptance criteria with reported device performance. It lacks the quantitative data and detailed methodology typically found in such a study.

Here's an analysis based only on the provided text, highlighting what is present and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a specific table of acceptance criteria nor reported device performance metrics in a comparative format. It makes a general claim:

Missing: Specific, measurable acceptance criteria (e.g., spatial resolution, DQE, contrast resolution, noise levels, etc.) and quantitative data demonstrating how the CRystalView T-Series met these criteria.

2. Sample Size Used for the Test Set and Data Provenance

The document does not provide any information regarding the sample size used for a test set, nor does it mention data provenance (e.g., country of origin, retrospective or prospective). It only refers to "Alara's laboratory and V&V testing."

3. Number of Experts Used to Establish Ground Truth and Qualifications

The document does not provide any information regarding the number of experts used to establish ground truth or their qualifications.

4. Adjudication Method

The document does not describe any adjudication method.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

The document does not mention or describe a multi-reader multi-case (MRMC) comparative effectiveness study. Therefore, no effect size of human readers improving with AI vs. without AI assistance is provided.

6. Standalone (Algorithm Only) Performance Study

The document does not describe a standalone performance study. The device itself is a Computed Radiography System, implying it produces images for human interpretation, rather than an AI algorithm for diagnosis.

7. Type of Ground Truth Used

The document does not specify the type of ground truth used for any testing.

8. Sample Size for the Training Set

The document does not mention a training set or its sample size. Given that this is a CR acquisition system and not an AI-based diagnostic algorithm, a "training set" in the context of machine learning is not applicable here. The device produces images, and the "training" involved would be for the internal algorithms responsible for image processing and reconstruction, which are typically developed using engineering and physics principles rather than a labeled medical image training set.

9. How Ground Truth for the Training Set Was Established

As there is no mention of a training set, the document does not describe how ground truth for a training set was established.

Summary of what is available from the text:

The provided 510(k) summary focuses on demonstrating "substantial equivalence" of the CRystalView T-Series Computed Radiography System to previously cleared predicate devices (K042023: Fuji Computed Radiography (FCR) ClearView CS Image Reader and K955643; DenOptix ALARA Imaging System). The claims of equivalence are based on "Alara's laboratory and V&V testing," which are stated to show that the performance characteristics and diagnostic capabilities are equivalent. However, without the underlying test reports, the specific acceptance criteria, quantitative results, and methodological details (like sample sizes, expert involvement, and ground truth establishment) cannot be extracted from this document. This level of detail is typically found in the full 510(k) submission and supporting validation documentation, not usually in the public summary.

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CRystalView R200 is indicated for use in generating radiographic images of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures.

The Alara CRystalView® R200 is a desktop Computed Radiography (CR) system designed to generate digital x-ray images by reading photostimulable phosphor image plates exposed using standard X-ray systems and techniques. The system consists of a CR Reader, a OC Workstation with software, cassettes, and image plates. Image data is sent via a dedicated connection from the Reader to the CRystalView R200 QC Workstation, where it is processed and displayed for review. The system outputs images and patient information to a PACS using the standard DICOM 3.0 protocol. The fully configured CRystalView R200 System includes acquisition console software and post-processing image enhancement software. A reseller may alternatively provide these two software components or appropriately cleared equivalents, as well as the QC Workstation hardware. The modification reported in this submission replaces the integrated third-party image enhancement software with image enhancement software developed by Alara.

The provided text describes a 510(k) submission for the Alara CRystalView® R200 Computed Radiography System. The submission focuses on demonstrating substantial equivalence to a predicate device after modifying the integrated image enhancement software.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample Size Used for the Test Set and Data Provenance:

• Sample Size for Test Set: The text does not explicitly state the specific number of images or cases used in the "confirmatory clinical concurrence study" or "clinical studies." It mentions "images" were judged by a radiologist, but not the quantity.
• Data Provenance: The text does not specify the country of origin of the data. It indicates the study was a "clinical concurrence study," implying prospective data collection for the purpose of comparing the two software versions, but does not explicitly state it was prospective. The context suggests it was to compare the newly implemented software against the previous, implying a comparison on clinical data.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:

• Number of Experts: The text states "a radiologist" was used to judge the images. This implies a single radiologist.
• Qualifications of Experts: The text identifies the expert as "a radiologist." No further details on their experience (e.g., years of experience) are provided.

4. Adjudication Method for the Test Set:

• Adjudication Method: The text indicates that images were "judged by a radiologist." It does not describe any specific adjudication method like 2+1 or 3+1, which are typically used when multiple readers are involved and their opinions differ. Given that only "a radiologist" is mentioned, no complex adjudication method seems to have been applied, or at least it is not detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of how much human readers improve with AI vs without AI assistance:

• MRMC Study: No, a multi-reader, multi-case comparative effectiveness study was not explicitly stated. The study described involved "a radiologist" judging images, suggesting a single-reader assessment rather than a multi-reader setup.
• Effect Size of AI Assistance: This study is not evaluating the improvement of human readers with AI assistance. It is comparing the performance of a new image enhancement software (developed by Alara) against an older, third-party image enhancement software, both integrated into a Computed Radiography (CR) system. The core of the study is about the equivalence of image processing software, not AI assistance for human readers.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done:

• Standalone Performance: The text does not explicitly describe a standalone (algorithm only) performance study of the image enhancement software. The clinical study involved a radiologist judging images, indicating a human-in-the-loop evaluation of the output of the system (which includes the image enhancement software). The "performance tests" mentioned alongside clinical studies could encompass some standalone technical evaluations (e.g., image quality metrics like spatial resolution, contrast-to-noise ratio), but the text focuses on diagnostic capabilities as judged by a human.

7. The Type of Ground Truth Used:

• Type of Ground Truth: The ground truth for the clinical study was based on expert consensus/opinion (specifically, the judgment of "a radiologist" regarding image quality ratings). There is no mention of pathology, outcomes data, or other objective measures being used for ground truth. The study aimed to assess the equivalence of perceived image quality.

8. The Sample Size for the Training Set:

• Sample Size for Training Set: The text does not provide any information regarding a training set size. The study described is a comparison of image enhancement software versions, not the development or training of a new algorithm requiring a distinct training dataset.

9. How the Ground Truth for the Training Set Was Established:

• Ground Truth for Training Set: As no training set is mentioned or implied, the method for establishing its ground truth is not applicable or provided in the text.

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CRystalView R200 is indicated for use in generating radiographic images of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures.

The Alara CRystalView® R200 is a desktop Computed Radiography (CR) system designed to generate digital x-ray images by reading photostimulable phosphor image plates exposed using standard X-ray systems and techniques. The system consists of a CR Reader, a QC Workstation with software, cassettes, and image plates. Image data is sent via a dedicated connection from the Reader to the CRystalView R200 OC Workstation, where it is processed and displayed for review. The system outputs images and patient information to a PACS using the standard DICOM 3.0 protocol. The fully configured CRystalView R200 System includes acquisition console software and postprocessing image enhancement software. A reseller may alternatively provide these two software components or appropriately cleared equivalents, as well as the QC Workstation hardware.

Here's a breakdown of the acceptance criteria and the study that proves the Alara CRystalView® R200 Computed Radiography System meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly state quantitative acceptance criteria in terms of specific performance metrics (e.g., sensitivity, specificity, spatial resolution, contrast-to-noise ratio requirements). Instead, it relies on a qualitative assessment of "substantial equivalence" to predicate devices. The primary performance criterion appears to be:

The device also demonstrated compliance with electrical, mechanical, EMC, and laser safety standards (though not directly image quality performance). Images are generated for human anatomy, replacing film/screen systems in general diagnostic procedures. |
| Compliance with applicable FDA and international safety standards. | "CRystalView R200 complies with applicable FDA and international standards pertaining to electrical, mechanical, EMC, and laser safety of medical and/or laser devices." |

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: The document states that clinical studies were performed, including a "confirmatory clinical concurrence study." However, it does not specify the sample size (number of images or patients) used in this clinical study.
• Data Provenance: The document does not explicitly state the country of origin of the data or whether it was retrospective or prospective. Given it's a clinical concurrence study comparing to a predicate, it would typically be prospective, but this is not explicitly confirmed.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• Number of Experts: The document states "images were judged by a radiologist." This implies a single radiologist was involved in the clinical concurrence study.
• Qualifications of Experts: The document explicitly states the expert was a "radiologist." However, it does not provide any further details on their qualifications (e.g., years of experience, subspecialty).

4. Adjudication Method for the Test Set

• The document indicates that images were "judged by a radiologist." With only one radiologist mentioned, an explicit adjudication method (like 2+1 or 3+1) is unlikely to have been used for discrepancies, as there were no multiple independent readers to adjudicate. So, the method would be "none" in the typical sense of adjudicating disagreements. The single radiologist's judgment served as the benchmark.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

• Yes, a comparative effectiveness study was done, though it involved a single reader. The study compared the CRystalView R200 to the Agfa ADC Compact.
• Effect Size: The document states, "Clinically, no statistically significant difference was found in image quality ratings of CRystalView R200 and the Agfa ADC Compact when images were judged by a radiologist." This implies the effect size was not statistically significant in terms of improved human reader performance with the new device compared to the predicate, as their image quality ratings were comparable. The goal was equivalence, not superiority.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

• The device being evaluated is a Computed Radiography System that generates digital X-ray images, which are then reviewed by a human. The "image quality ratings" mentioned are judgments by a radiologist, implying human-in-the-loop performance evaluation.
• While the system has acquisition console software and postprocessing image enhancement software, the document does not describe any standalone algorithm-only performance evaluation independent of human interpretation for diagnostic purposes. The focus is on the human interpretation of the images produced by the system.

7. The Type of Ground Truth Used

• The ground truth in this study appears to be expert consensus (from a single radiologist, acting as the expert) on "image quality ratings." It is not based on pathology, outcomes data, or a gold standard that is independent of image interpretation. The comparison is between images of the new device and the predicate, as interpreted by an expert.

8. The Sample Size for the Training Set

• The document does not provide any information regarding a training set or its sample size. This is a medical device clearance submission (510(k)), which typically focuses on demonstrating equivalence to a predicate, not necessarily on detailing the developmental process, including machine learning model training sets.

9. How the Ground Truth for the Training Set Was Established

• As no information about a training set is provided, there is no information on how its ground truth was established.

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CRystalView is indicated for use in generating radiographic images of human anatomy. It is intended to replace radiographic film/screen systems in all general-purpose diagnostic procedures.

The Alara CRystalView™ is a Desktop Computed Radiography (CR) System designed to generate digital x-ray images by scanning photo-stimulable storage phosphor imaging plates exposed using standard X-ray systems and techniques. The system consists of a CR Reader, a OC workstation with software, cassettes, and imaging plates. Image data is sent via a dedicated connection from the Reader to the CRystalView QC Workstation, where it is processed and displayed for review. The system outputs images and patient information to a PACS using the standard DICOM 3.0 protocol. The fully configured CRystalView System includes acquisition console software and post-processing image enhancement software. A reseller may alternatively provide these two software components or appropriately cleared equivalents, as well as the QC Workstation hardware.

Here's an analysis of the provided text to extract the acceptance criteria and study details:

1. A table of acceptance criteria and the reported device performance

The provided text does not explicitly state quantitative acceptance criteria in a table format. However, it implicitly defines the acceptance criteria as demonstrating substantial equivalence to predicate devices. The performance is reported in terms of comparability.

Notes on Acceptance Criteria:

• The primary acceptance criterion is substantial equivalence to the predicate devices (PhorMax Eagle Scanner (K001499) and Agfa ADC Compact (K974597)).
• For clinical performance, the key metric for image quality was "no statistically significant difference" compared to a predicate device.

2. Sample size used for the test set and the data provenance

• Sample Size for Test Set: The document does not specify the exact number of images or cases used in the clinical concurrence study. It only states that "a clinical concurrence study" was carried out, where "images were judged by a radiologist."
• Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Number of Experts: "a radiologist" (singular, implying one radiologist).
• Qualifications of Experts: The specific qualifications (e.g., years of experience, subspecialty) of the radiologist are not provided.

4. Adjudication method for the test set

• Adjudication Method: Not explicitly stated. Given that only "a radiologist" was mentioned, it suggests a single-reader assessment rather than a multi-reader adjudication method (like 2+1, 3+1).

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance?

• MRMC Study Conducted: No, an MRMC study was not conducted. The study described is a "clinical concurrence study" where images from the CRystalView and a predicate device (Agfa ADC Compact) were judged by a single radiologist for image quality.
• Effect Size: Not applicable, as this was not an MRMC study nor an AI-assisted study. The device itself (CRystalView) is a Computed Radiography (CR) system, not an AI-based diagnostic tool for assisting human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Standalone Performance: Yes, implicitly. The performance of the CRystalView system itself (the algorithm and hardware) was evaluated through laboratory and clinical studies. The "image quality ratings" of the CRystalView were compared to those of the predicate. This is a standalone evaluation of the device's output quality.

7. The type of ground truth used

• Type of Ground Truth: "Image quality ratings... judged by a radiologist." This implies expert consensus (or in this case, expert judgment by a single radiologist) was used to establish the "ground truth" for image quality comparison. It's not pathology or outcomes data.

8. The sample size for the training set

• Sample Size for Training Set: Not mentioned or applicable. This documentation focuses on the validation of the device and does not describe the development or training of any machine learning component. The CRystalView system described here is a Computed Radiography system for image generation, not an AI diagnostic algorithm that requires a "training set" in the conventional machine learning sense.

9. How the ground truth for the training set was established

• Ground Truth for Training Set: Not applicable, as this device does not describe an AI/ML algorithm requiring a training set with established ground truth.

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